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Optimising Preeclampsia First-Trimester Screening Using Three Parameters
Shehla Baqai1,2, Shazia Tufail1,2, Anam Waheed
1Department of Gynaecology and Obstetrics, CMH Lahore Medical College and Institute of Dentistry, National University of Medical Sciences, Lahore, Pakistan.
Insights
The Fetal Medicine Foundation (FMF) algorithm showed a 38% detection rate for preeclampsia, which is better than using maternal risk factors alone. Further adjustments may improve its predictive accuracy for this condition.
Area of Science:
- Obstetrics and Gynecology
- Maternal-Fetal Medicine
- Clinical Prediction Modeling
Background:
- Preeclampsia (PE) is a significant cause of maternal and fetal morbidity.
- Early prediction of PE is crucial for timely intervention and improved outcomes.
- Current risk assessment strategies have limitations in accurately identifying high-risk pregnancies.
Purpose of the Study:
- To evaluate the predictive performance of the first-trimester Fetal Medicine Foundation (FMF) screening algorithm for preeclampsia.
- To compare the algorithm's accuracy against prediction solely based on maternal risk factors.
Main Methods:
- An observational study was conducted with 100 pregnant women at gestational age < 13 weeks.
- The FMF screening algorithm incorporated maternal characteristics, mean arterial pressure, and uterine pulsatility index.
- Participants were followed until delivery to ascertain PE development and fetomaternal outcomes.
Main Results:
- The FMF algorithm categorized 22% of patients as high-risk.
- Preeclampsia developed in 13 patients.
- The algorithm achieved a 38% detection rate, 75% diagnostic accuracy, and a 20% false positive rate at a 1:100 risk cut-off.
Conclusions:
- The adapted FMF algorithm demonstrated a low but superior performance compared to maternal risk factors alone in predicting preeclampsia.
- Further improvements in detection rates may be achieved by adjusting for additional factors or ethnicity-specific values.
Objective:
To evaluate the performance of first-trimester preeclampsia-screening algorithm in predicting preeclampsia (PE).
Study Design:
Observational study. Place and Duration of the Study: Department of Obstetrics and Gynaecology, Combined Military Hospitals (CMH) Lahore, Pakistan, between 1st January and 31st August 2022.
Methodology:
Data of 100 women of any parity aged 18-35 years at gestational age < 13 weeks based on the last menstrual period (LMP), was analysed. First trimester Fetal Medicine Foundation (FMF) screening algorithm for preeclampsia was used entering maternal characteristics, mean arterial pressure and uterine pulsatility index only, for risk calculation. Patients were followed up till delivery for the development of preeclampsia and fetomaternal outcomes. Clinical characteristics of women with and without preeclampsia were compared using the Chi-square and independent samples t-test.
Results:
The mean age of patients was 29.29±4.56 years and 60% were nullipara. Seventy-eight patients were placed in the low-risk category and 22 patients were in the high-risk category according to the FMF algorithm. Preeclampsia developed in 13 patients. For a risk cut-off of 1 in 100, the FMF algorithm showed a detection rate of 38% with diagnostic accuracy of 75% and a false positive rate (FPR) of 20%.
Conclusion:
Although the performance of adapted FMF algorithm to predict preeclampsia gestational was low, it was found superior to prediction by maternal risk factors alone. Adjustment for additional factors or ethnicity-specific values may help in further improvement of detection rate.
Key Words:
Blood pressure, Biomarkers, Biological markers, Preeclampsia, Risk assessment.
